Chronic obstructive pulmonary disease (COPD) and asthma are traditionally considered as two separate diseases. However, between 15-45% of COPD patients additionally report a history of asthma. Subjects with both COPD and asthma are an important clinical subgroup, with increased symptoms, exacerbations and hospitalizations. COPD can be readily diagnosed using spirometry, yet there is no gold standard test for asthma. Therefore, recent guidelines have provided a list of largely clinical features to identify patients with the asthma-COPD overlap syndrome (ACOS). We hypothesize that improvements in phenotype definition will be required to make progress in population studies of the epidemiology and genomics of ACOS. However, few large cohorts are amenable to this investigation. In the Genetic Epidemiology of COPD Study (COPDGene), our group has identified clinical, imaging, and genetic features of ACOS, defined by questionnaire. In this proposal, we will address the phenotyping and genomics of ACOS through the following Specific Aims. (1) Peripheral blood biomarkers of the ACOS phenotype: We will test the hypothesis that asthma biomarkers can improve the definition of ACOS. We will measure total and specific Immunoglobulin E (IgE) levels in COPDGene. Blood eosinophil counts are being measured in phase 2 of COPDGene. We will examine baseline and longitudinal clinical and chest CT imaging features of ACOS subjects with allergic sensitization and/or peripheral eosinophilia compared to usual COPD. (2) Gene expression in ACOS: We will test the hypothesis that ACOS has distinct biologic influences compared to usual COPD. We will perform RNA sequencing on peripheral blood samples to identify differentially expressed transcripts in ACOS subjects with allergic sensitization or peripheral eosinophilia compared to usual COPD. We will integrate the RNA-seq results with genomewide single nucleotide polymorphism (SNP) data to identify eQTL SNPs associated with transcript levels of the differentially expressed genes. (3) Systems genomics in ACOS: We will test potential functional mechanisms and genetic regulatory effects important in ACOS, identified using network methods. In sub-aim (a), we will construct gene networks using the RNA-seq data, compare regulatory connections in ACOS and usual COPD, and identify the genes most central to the differences between these networks. In sub-aim (b), we will perform in vitro validation of the networks using siRNA knockdown of key genes in lymphoblastoid cell lines from subjects with ACOS and usual COPD. Using asthma biomarkers and RNA-seq data to discover genetic influences on the clinically-relevant asthma-COPD overlap syndrome could identify objective diagnostic markers of ACOS or novel pathways and targets, moving towards the goal of precision medicine in COPD. The large-scale biomarker and RNA-seq datasets will serve as resources for COPDGene and the community of COPD investigators.